The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …

One of the important factors affecting micro-video recommender systems is to model the
multi-modal user preference on the micro-video. Despite the remarkable performance of …

Reorganizing implicit feedback of users as a user-item interaction graph facilitates the
applications of graph convolutional networks (GCNs) in recommendation tasks. In the …

Modeling user's long-term and short-term interests is crucial for accurate recommendation.
However, since there is no manually annotated label for user interests, existing approaches …

Recommendation is a prevalent and critical service in information systems. To provide
personalized suggestions to users, industry players embrace machine learning, more …

Video platforms have become indispensable components within a diverse range of
applications, serving various purposes in entertainment, e-learning, corporate training …

This chapter studies state-of-the-art research related to multimedia recommender systems
(MMRS), focusing on methods that integrate multimedia content as side information to …

Due to the continuous booming of surveillance and Web videos, video moment localization,
as an important branch of video content analysis, has attracted wide attention from both …

The micro-video recommendation system becomes an essential part of the e-commerce
platform, which helps disseminate micro-videos to potentially interested users. Existing …

Recently, micro-video sharing platforms such as Kuaishou and Tiktok have become a major
source of information for people's lives. Thanks to the large traffic volume, short video …